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TAIMS: Transparent Adaptation in Intelligent Multimodal HumanMachine Systems

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Title: TAIMS: Transparent Adaptation in Intelligent Multimodal HumanMachine Systems


1
TAIMSTransparent Adaptation in Intelligent
Multimodal Human-Machine Systems
  • project startMay 2002

2
team
Karon MacLean, Lead Kathleen Akins Cristina
Conati Sidney Fels Dinesh Pai Ronald Rensink
UBC Computer Science SFU Philosophy UBC Computer
Science UBC Elect. Computer Eng. UBC Computer
Science UBC Psych, Comp. Sci
3
backgroundinterface transparency
  • users efforts are entirely directed at a
    task,and not at the interfacethat supports the
    task.
  • user and machine forma seamless system

4
interface transparency
  • perceptual transparencyinformation is absorbed
    without conscious attention (key may be rapid
    sensory responses)
  • attentional transparencysystem directs
    attention to whats important without effort or
    disruption
  • task transparencyappropriate information is
    supplied as user needs it

5
objectives
  • design and evaluate user interfaces that adapt
    conscious and nonconscious user feedback
  • study the interplay between conscious and
    nonconscious processing
  • create a state-of-the-art realtime platform to
    support 1 2

6
objective 1 (ultimate goal)design and evaluate
user interfaces that adapt conscious and
nonconscious user feedback
  • Explore potential for lowering overall user
    effort by shifting user engagement from conscious
    to nonconscious modes.
  • User models updated through low-latency biometric
    sensing and interpretation of user state and
    interaction context
  • Rely on context-sensitive thresholds determined
    in 2)

7
objective 2study the interplay between
conscious and nonconscious multimodal processing
  • Determine process characteristics in visual,
    auditory and haptic domains
  • thresholds for transparency in each modality
  • how modalities interact
  • map intelligence of nonconscious processing

8
objective 3create a state-of-the-art realtime
platform
  • Build a research tool to support 1 and 2
  • fast local network cluster
  • coordinates sensor display servers with data
    and user model servers
  • high communication bandwidths
  • supports variety of refresh rates, platforms

9
approach
developrealtimeplatform
developuser models prototypeapplications
conductpsychophysicsexperimentsin
multimodalperceptualprocessing
time
10
status
  • just starting
  • Ben Forsyth (M.Sc., CS)beginning work on
    realtime platform
  • multimodal experiments being planned
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